#mult_product = np.zeros((len(vector_data), len(vector_data)))
#
#
#    
#
#    
#for i in xrange(0, len(vector_data)):
#    for j in xrange(0, len(vector_data)):
##        print sum(vector_data[i] * vector_data[j])
#        mult_product[i,j] = LM(vector_data[i], vector_data[j])#sum(vector_data[i] * vector_data[j]) / float(sum(vector_data[i]))
#        
##pcolor(mult_product)
##colorbar()
##yticks(arange(0 + 0.5,len(cov_mat) + 0.5),range(0,len(cov_mat)))
##xticks(arange(0 + 0.5,len(cov_mat) + 0.5),range(0,len(cov_mat)), rotation=90)
##ylim(0, len(cov_mat))
##xlim(0, len(cov_mat))
##title('Covariance matrix')
##tick_params(axis='y', which='major', labelsize=4)
##tick_params(axis='x', which='major', labelsize=4)
##savefig('covariance.pdf')
##show()
##close()